Active noise cancellation techniques are well-known in the art. In-ear and circumaural headphones generally exhibit good passive filtering of high-frequency ambient noise. However, this passive filtering is typically not effective for low-frequency (500 Hz or less) ambient noise. Active noise cancellation techniques are well-known as a means for dealing with low-frequency ambient noise in headphones and other audio devices. Generally, active noise cancellation is achieved by measuring the ambient noise and then emitting a copy of the noise signal that has been inverted, or made completely out-of-phase, to thereby cancel the noise signal at the hearing of the listener.
The most common approach used in this area is feed-forward, active cancellation method. Ambient noise is measured, inverted, and then added to the intended audio content in order to attenuate the ambient noise present at the ear drum of the listener. However, in many applications, considerable acoustic and electrical delay between the ambient noise measured and the inverse noise may turn an intended cancelling effect (anti-phase) into an additive effect (in-phase). This delay is particularly a problem for high-frequency ambient noise where the signal phase shift is higher and therefore results in an additive and audible ‘whizzing’ noise. It is therefore common in the art to filter out the inverted high-frequency ambient noise through a low-pass filter before it is reproduced in the earphone. Further, active, feed-forward noise cancellation is frequently implemented in headphone devices through the use of simple, inverting analog filters to approximate the headphone acoustic response.
Modern, portable low-power audio ICs are becoming fully-integrated, audio devices with digital signal processing (DSP) cores in which all mixing and audio processing is performed digitally. Audio signals, including the measured noise, are first converted into digital signals using high-fidelity analog-to-digital converters (ADC or A/D converters). The digital noise is processed and mixed in the DSP to generate an anti-noise signal, which is then reproduced in analog via a high-fidelity digital-to-analog converter (DAC or D/A converter). Both A/D and D/A converters are typically of the oversampled, sigma-delta (SD) type. These A/D and D/A SD converters achieve high-fidelity conversion with quantization noise-shaping by oversampling the relatively low-frequency audio signal N-times above the Nyquist rate, fs. The A/D converter digital output is later down-sampled from a low-resolution digital word running at N-times fs to a high-resolution digital word running at fs. The DSP typically runs at this lower sampling rate of fs to save power. Subsequently, when DSP processing is completed, the high-resolution word running at fs is converted back to a low-resolution digital word running at M times fs. The digital anti-noise signal is then converted, via D/A converter, back to an analog anti-noise signal.
Prior to DSP processing, the digital noise signal is converted to a higher resolution/lower frequency using a decimation filter. This decimation filter is typically implemented in two stages: (1) a cascaded integrator-comb CIC filter and (2) a chain of finite-impulse response (FIR) filters. The CIC filter down-samples the data words running at N times fs to an intermediate multiple of fs with notches around the aliasing frequencies, while the FIR filters remove any remaining high-frequency quantization noise introduced by the SD ADC. After DSP processing, the digital anti-noise signal is converted to a lower resolution/higher frequency using an interpolation filter. The interpolation filter typically consists of a cascade of FIR filters, followed by an up-sampler (e.g., a zero-stuffer or a zero-order hold). The FIR filters remove the up-sampled images of the signal bandwidth that would otherwise fold around the aliasing frequencies at the output of the D/A converter. The number of filtering stages required at either end (i.e., decimation or interpolation) depends on the oversampling ratio (OSR) and the order of quantization noise shaping of the SD converter.
Unfortunately, the decimation filtering and interpolation filtering necessary to perform the anti-noise signal processing in the DSP introduces large signal processing delays. These delays make the DSP core audio code architecture unsuitable for feed-forward active noise cancellation. An analog bypass path may be used to bypass the decimation and interpolation filtering steps. However, the use of an analog bypass path is expensive in terms of device complexity, area, and power.
It is therefore very useful to provide a low delay, digital bypass path to improve active noise cancellation performance. A digital bypass path potentially eliminates the need for a number of FIR filters, CIC filters, up-samplers, and a sigma-delta modulator for a DAC. A digital bypass path makes it possible to implement more complex and accurate filter responses in digital technology to thereby compensate for acoustic effects in forward active noise cancellation. A digital bypass path potentially allows direct trade-off of parameters, such as gain resolution, filter coefficient resolution and complexity, for reduced delay.